A model of local field potentials generated by medial superior olive neurons (Goldwyn et al 2014)

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A computational model of local field potentials generated by medial superior olive neurons. These field potentials are known as the "auditory neurophonic". MSO neuron is modeled as a soma and two dendrites (following Mathews et al, Nature Neurosci, 2010). Intracellular and a 1D extracellular domain are dynamically coupled and solved to simulate spatial-temporal patterns of membrane voltage and extracellular voltage in response to trains of synaptic inputs (monolateral or bilateral, excitation and/or inhibition). The model produces spatio-temporal patterns similar to neurophonic responses recorded in vivo, as discussed in the accompanying manuscript.
1 . Goldwyn JH, Mc Laughlin M, Verschooten E, Joris PX, Rinzel J (2014) A model of the medial superior olive explains spatiotemporal features of local field potentials. J Neurosci 34:11705-22 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Medial Superior Olive (MSO) cell;
Channel(s): I h; I_KLT;
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s): Evoked LFP;
Implementer(s): Goldwyn, Joshua [jhgoldwyn at gmail.com];
Search NeuronDB for information about:  I h; I_KLT;
%%% THIS CODE CALLS MSO_dae.m %%%

% Computes Vm of MSO neuron model and Ve in extracellular "virtual cylinder"
% Accompanies the manuscript [submitted to J. Neuroscience]:
% "A model of the medial superior olive explains spatiotemporal features of local field potentials"
% JH Goldwyn, M Mc Laughlin, E Verschooten, PX Joris, J Rinzel
% MSO model neuron was introduced in:
% "Control of submillisecond synaptic timing in binaural coincidence detectors by Kv1 channels"
% Paul J Mathews, Pablo E Jercog,	John Rinzel, Luisa L Scott, Nace L Golding
% Nature Neuroscience 13 601-609 (2010)

% Simulation code by Joshua H Goldwyn
% Submitted to ModelDB 1/14/13 by Joshua H Goldwyn [jgoldwyn@nyu.edu]

close all
clear all

%%% Set Parameters %%%
tEnd = 7.;             % simulation duration [ms]
stimType = 'left';     % monolateral excitation
gE = 10;               % excitatory conductance [mS / cm2]
tauE = 0.2;            % excitatory time constant (alpha function) [ms]
csynE = [2 22];        % location of excitation (compartment number)
gI = 0;                % inhibitory conductance [mS / cm2]
tauI = [.4 2];         % inhibitory time constants (double exponential function) [ms]
csynI = [12];          % location of inhibition (compartment number)
synFreq = [500 501]; % EPSP frequency (Hz) for each dendrite. inhibition freq is first entry
synDelay = [.0 .0];    % Delay of EPSP onset times in each dendrite [ms]
inhibDelay = 0;        % Delay of inhibition relative to excitation in first entry of synDelay
FreezeKLT = 0;         % Whether to Freeze KLT conductance at rest (0=No)
rB = 11;               % radius of extracellular virtual cylinder (must be larger than soma radius = 10) [micro m]

%%% Run model %%%
out = MSO_dae(tEnd, stimType, gE, tauE, csynE, gI, tauI, csynI, synFreq, synDelay, inhibDelay, FreezeKLT, rB);

%%% Surface Plot results %%%
% NOTE: Ve is not extended to ground, x-dimension is size of the neuron model
surf(out.x,out.t,out.Vm), shading('flat')
xlabel('Distance from soma (\mum)')
ylabel('Time (ms)')
zlabel('Vm (mV)')
title('Membrane Potential','FontSize',24)

surf(out.x,out.t,out.Ve), shading('flat')
xlabel('Distance from soma (\mum)')
ylabel('Time (ms)')
zlabel('Ve (mV)')
title('Extracellular Potential','FontSize',24)

set(gcf,'position',[25         291        1399         404])

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